Performance of RegCM4 simulations over Croatia and adjacent climate regions
We investigate the impact of horizontal resolution, convection parameterization and lateral boundary conditions on the ability of a regional climate model ‐ RegCM4 to simulate the observed temperature and precipitation climatology over Croatia and surrounding regions. An ensemble of RegCM4 simulatio...
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Veröffentlicht in: | International journal of climatology 2020-11, Vol.40 (14), p.5843-5862 |
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Sprache: | eng |
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Zusammenfassung: | We investigate the impact of horizontal resolution, convection parameterization and lateral boundary conditions on the ability of a regional climate model ‐ RegCM4 to simulate the observed temperature and precipitation climatology over Croatia and surrounding regions. An ensemble of RegCM4 simulations over Europe has been generated including two resolutions (50 and 12.5 km), two different deep convection schemes and different boundary conditions (a reanalysis and four global climate models). Using two observational data sets (with and without the undercatch correction) shows that the magnitude of RegCM4 errors in winter precipitation also depends on observational uncertainty. While the mean precipitation amounts in high‐resolution simulations are generally overestimated in the cold part of the year, low‐resolution RegCM4 simulations are comparable to most of other EURO‐CORDEX models. When forced by ERA‐Interim, RegCM4 performs relatively poorly in reproducing temporal correlations against observations, but performs well in terms of spatial correlation. Whereas precipitation amounts from high‐resolution simulations need further improvements, the RegCM4 skill in simulating near‐surface temperature is high and well suited for impact studies.
Our experiments using RegCM4 show that different convection schemes and horizontal resolutions can both improve and deteriorate different aspects of model performance. No model configuration was clearly superior to the others. This result points out the difficulty of selecting an optimal model configuration for a given region, an exercise which requires careful experimentation. |
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ISSN: | 0899-8418 1097-0088 |
DOI: | 10.1002/joc.6552 |